Machine Learning Data Scientist

The Machine Learning Data Scientist will be primarily responsible for design, execution and delivery of exploratory concepts, rapid prototypes, and pilot solutions designed to test hypothesis and incubate transformative new capabilities by applying Machine Learning, data mining techniques, doing statistical analysis, and building high quality prediction systems. Key activities will consist of optimizing existing and new business process with the use of Machine Learning and data analysis, guiding and approving the appropriate technology to fit the requirements, and building a quick prototype or pilot to support the hypothesis. Primary responsibilities include leading research and development of statistical learning models for data analysis; design and build predictive models and algorithms for experimentation and eventual adaption within the enterprise; documenting and articulating solution architecture and lessons learned for each exploration and accelerated incubation; encouraging new transformative thinking, trail blazing, and facilitate imagination and ideation sessions; maintaining current knowledge of technology landscape and emerging developments; employing practical approach to incubation and eventual platform integration; driving and orchestrating external partner or vendor collaboration to satisfy the needs of any given exploration; working with dedicated Innovation team and with various other Product and Enterprise teams to execute explorations as part of accelerated incubation of new capabilities and ensuring alignment, knowledge transfer and transition of proven concepts and incubated capabilities to Product and to the Enterprise teams across Walgreens Boots Alliance for productization and scaled up operationalization.This role requires an imaginative, creative mind set with substantial hands-on experience in utilizing, exploring and adopting technologies to build viable and innovate solutions, while working within a global team, and adhering to delivery excellence for execution and lifecycle management. The successful candidate will be will be a Data Science and Machine Learning generalist who is experienced and successful with innovation, understands how to adopt their technology in the Enterprise and understands how to move take advantage trends and technologies to test hypotheses, prove feasibility, viability and fail fast.

Job Responsibilities

Develops algorithms to determine relevant products, drugs, and content to display to users. Develops and maintains the end to end A/B testing plans including strategy, roadmap, and execution. Analyze search patterns and customer behaviors to inform strategies

Leads personalization efforts by incorporating customer models and site data.

Influences product decisions for internal tools that support search relevancy.

Performs as the subject matter expert for the specified functional area and may become actively involved, as required, to meet schedules and resolve problems highly complex in nature.

Develops highly complex programs that establish and enhance standards. Develops the specifications of highly complex projects and may perform as implementation project lead.

Develops and executes operational activities that have moderate to significant impact on the direction of the specified functional area and/or the organization, and may include responsibilities, such as:

*Develops the highly- complex or industry- approaches to drive the development of broad reaching strategies.

*Defining, deploying and institutionalizing functional area research approaches and related knowledge basis. *Forecasting and assessing industry trends and their impact on designs and methods of the specified functional area.

Shares complex information related to areas of expertise and/or to gain acceptance of new or enhanced business solutions. "Evangelizes" new ideas / solutions to gain acceptance from a wide range of audiences

Develops business approaches and new or enhanced processes.

Guides and mentors a wide range of audiences. May provide subject matter expertise to the business. May participate in teaching and training members of the work team.

Walgreens, one of the nation's largest drugstore chains, is included in the Retail Pharmacy USA Division of Walgreens Boots Alliance, Inc., the first global pharmacy-led, health and wellbeing enterprise. More than 10 million customers interact with Walgreens each day in communities across America, using the most convenient, multichannel access to consumer goods and services and trusted, cost-effective pharmacy, health and wellness services and advice. Walgreens operates 8,175 drugstores with a presence in all 50 states, the District of Columbia, Puerto Rico and the U.S. Virgin Islands. Walgreens omnichannel business includes Walgreens.com. Approximately 400 Walgreens stores offer Healthcare Clinic or other provider retail clinic services.

As the neighborhood drugstore and retailer, our goal is to make health and happiness simpler, easier and within reach. And we remain a trusted wellness provider offering convenient access to important health services, such as immunizations and an array of pharmacy services that can help patients improve their health. To our team members, Walgreens represents a unique opportunity to excel in their careers in a welcoming and inclusive environment. We offer the chance to work in a truly supportive environment, and be a part of a progressive organization dedicated to the well-being of our customers, team members and the communities we all call home.

Basic Qualifications

Bachlerâ&#128;&#153;s degree in a quantitative field such as Computer Science, Statistics or Mathematics and at least 5 years of experience in data science OR a High School Diploma/GED and at least 8 years of experience in data science.

Experience establishing & maintaining relationships with individuals at all levels of the organization, in the business community & with vendors.

Experience using time management skills such as prioritizing/organizing and tracking details and meeting deadlines of multiple projects with varying completion dates.

Experience analyzing and reporting data in order to identify issues, trends, or exceptions to drive improvement of results and find solutions.